Chapter 9

Question 1

Different approaches within qualitative data analysis: (9)

Answer 1

• Ethnographic accounts- Largely descriptive; Focuses on the way of life of particular individuals, groups, or organizations.
• Life histories- analyzing a person(s) background(s)- collections of stories around common themes and comparisons of those themes.
• Narrative analysis- Identifies: basic theory, construction, intention, and meaning of the story.
• Content analysis- Content and context analyzed.
• Conversation analysis- focuses on the structure and linguistic systems within the conversation.
• Discourse analysis- the study of written, spoken, or sign language. Analyzes the structure and in more detail than one sentence.
• Analytic induction- creating and testing hypotheses concerning each example studied.
• Grounded theory- Generation of analytical categories and their dimensions, and the identification of relationships between them
• Policy and evaluation analysis- Targeted towards analyzing the context behind social policies and programs and the effectiveness of their delivery and impact.

Question 2

Software can be categorized in 5 different groups:

Answer 2

1. Text retrievers- the searching of large amounts of data for instances of words and phrases.
2. Textbase managers- Similar to text retrievers, the textbase managers provide a structure to the data stored and are usually searchable.
3. Code and retrieve programs- Allow you to label or tag passages of text that can later be retrieved according to the codes applied.
4. Code based theory builders- support the conceptualization of data by the analyst and may also have extended hyperlinking facilities so that the researcher can create links between different aspects of the data set.
5. Conceptual network builders- programs which facilitate the graphic display and investigation of conceptual, cognitive or semantic networks within a data set.

Question 3

There are 3 stages in analyzing a piece of text:

Answer 3

1. Data management- Meaning is associated to things. Data is labeled, sorted, and brought together. Themes and concepts are identified in this section/
2. Descriptive accounts- aggregated data identifies key dimensions, then a descriptive account is linked to it. The diversity of the phenomenon is mapped, typologies may emerge in this stage.
3. Explanatory accounts- looks for patterns of association and relationships within data. Examining why these associations exist.